CATs: Semantic Correspondence with Transformers
CATs Semantic Correspondence with Transformers Our model CATs is illustrated below: git clone https://github.com/SunghwanHong/CATs cd CATs conda create -n CATs python=3.6 conda activate CATs pip install torch==1.8.0+cu111 torchvision==0.9.0+cu111 torchaudio==0.8.0 -f https://download.pytorch.org/whl/torch_stable.html pip install -U scikit-image pip install git+https://github.com/albumentations-team/albumentations pip install tensorboardX termcolor timm tqdm requests pandas Download pre-trained weights on Link All datasets are automatically downloaded into directory specified by argument datapath Result on SPair-71k: (PCK 49.9%) python test.py –pretrained “/path_to_pretrained_model/spair” –benchmark spair Result on SPair-71k, feature backbone frozen: (PCK […]
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